Communication networks are growing in both size and in the number of different services being provided by the communication networks. The amount of traffic generated by the different services is constantly growing. Customers or users of the services being provided by the communication networks expect the respective services to be delivered fast and without failures, or as few failures and delays as possible.
In order for operators to ensure a good usage of that network capacity and thus to keep delays to a minimum and the number of failures to a minimum, the communication networks are monitored more and more intensely and rigorously in order to both maximise network performance and to quickly discover any failure so that such a failure may be repaired or remedied swiftly.
Large-scale measurements of access network performance are becoming more popular as well as important in the data- and telecommunications industry. This has been recognized by the Internet Engineering Task Force, IETF. At IETF 86 in Orlando (March. 2013) there was a BoF on the topic (LMAP—Large-scale Measurements of Access network Performance).
Large-scale measurements impose several ongoing measurements at the same time. Some measurements consume a high amount of network capacity (e.g. Iperf which is a commonly used network testing tool that can create TCP and UDP data streams and measure the throughput of a network). Such network measurements may conflict with each other in different networks where lots of links are shared between customers. Further, some links may become bottlenecks due to the measurements themselves.
Active probing has long been an accepted method for determining performance parameters of packet-switched networks. The basic concept is to transmit probe packets from a sender towards a receiver. Each probe packet may be time stamped on both sides. The measurement endpoint (MEP) and measurement intermediate point (MIP) functionality and capabilities depends on the network technology deployed.
Existing work on admission control for measurements are primarily based on “earliest deadline first” scheduling. That is, they try to optimize a measurement schedule based on measurement requirements. There are several drawbacks of such solutions:                The scheduling may be too restrictive. For low-overhead measurements of metrics such as delay a measurement system must allow multiple simultaneous measurements.        The computational overhead is significant, in terms of recalculating the Earliest Deadline First, EDF, schedule, when measurement nodes comes and goes (e.g. down for maintenance). Re-calculation is necessary to avoid unused time slots for measurements.        The scheduling of measurements has to be performed at a centralised location.        Complex deployment, any change of a measurement schedule mandates having to update schedule on all measurement nodes.        
As described above, measurements that are performed in a large-scale may influence each other and hence reduce the credibility of the results. Further, if no measurement admission control is present some segments of the network may be overloaded due to measurements.